Urban network morphometrics (UNeMos) is a research technique and a design decision aid in urban design. UNeMOS are network science-based configurational metrics of urban morphology that can inform urban designing decision-making, helping designers to discriminate between different 2D and 3D design options. However, some UNeMOS differ from the standard link/node network encoding by using a transport network’s specific encoding, thus lacking usability in mainstream transport and transport geography and analytical power in 3D. There is also a lack of comparison between these encodings and whether the transport geography combination of standard encoding/closeness centrality analysis using Euclidean, angular, or combination thereof are as discriminant or more of urban design network layout in 2D and 3D. The commentary addresses this research gap by reflecting on how the research original contributions reported in the collected publications have deployed diverse combinations of transport network encoding and spatial models of distance to evaluate the values of transport network configuration. The commentary critically contextualises the publications’ original contributions with reference to a leading research question and a sub-question:
How well does UNeMOS, as a standard link/node spatial model and nonstandard spatial model, discriminate urban network configurations in 2D or 3D to capture urban design values?
The publications cover urban morphology, form, property pricing, transport planning, spatial distribution, high-density city areas, urban design, and network analysis. The publications demonstrate a deep understanding of various aspects of intra-urban and urban studies, including historical morphological roots, challenges for future research, and their practical applications in urban design and planning.
The methods employed in these studies involve a variety of quantitative and qualitative approaches. These include, among others, hedonic pricing modelling, multivariate models, road and metro network encoding, 2D and 3D spatial Design Network Analysis (sDNA) software, pedestrian standard path centre line network encoding, and value-based urban design. These methods have investigated the association between urban morphology, property prices, transport access, land-use resources, and pedestrian flows in contrasted urban contexts.
The approaches in the publications demonstrate a comprehensive understanding of the complexities and interdependencies in intra-urban and urban studies. The research explores various spatial scales, from local urban design to macro-meso transport planning, and investigates the relationship between outdoor and indoor 3D pedestrian networks in high-density urban areas.
Overall, the breadth and depth of the research in these publications and their original contributions showcase a strong foundation in intra-urban and urban studies, highlighting the importance of understanding urban environments’ spatial, socioeconomic, and morphological aspects for effective planning and design.
Summary of the publications and contributions:
Publication 1: Chiaradia, A., 2019. Urban Morphology/Urban Form. In: A. Orum, ed. The Wiley Blackwell Encyclopedia of Urban and Regional Studies. Hoboken, NJ: WileyBlackwell, pp. 1-6.
The paper contextualises and traces succinctly, from 1830 to 2019, the historical roots of urban morphology, including street network focus. The article provides a general introduction to critical concepts. Space syntax is contextualised as performative urban morphology and referenced to the early work of Stübben (1911).
The main contribution is the identification of three key challenges for future research: epistemological embedding, qualitative ontology, and a unified approach that bridges descriptive/explanatory and prescriptive/normative aspects.
Publication 2: Chiaradia, A.*, Hillier, B., Schwander, C. and Barnes, Y., 2013.
Compositional and urban form effects on residential property value patterns in Greater London. Proceedings of the Institution of Civil Engineers-Urban Design and Planning, 166(3), pp.176-199.
This research used a hedonic pricing modelling framework. The road network encoding uses standard road centre line encoding transformed by space syntax software and centralities metrics quantitative spatial characterisation of road network shape/accessibility to investigate the association with property price of a large sample of adjacent properties (≈100,000). Findings are aligned with extant theory related to the hedonic modelling of the residential property price; dwelling size is the most important.
The research reveals the importance of road network shape and accessibility characteristics in determining residential property prices in Greater London. The main contribution is the identification of two spatial scales associated with property prices: a local urban design scale (= 2,000 m).
Publication 3: Chiaradia, A.*, Hillier, B., Schwander, C. and Wedderburn, M., 2012. Compositional and urban form effects on centres in Greater London. Proceedings of the Institution of Civil Engineers-Urban Design and Planning, 165(1), pp.21-42.
This research used a multi-variate model, using standard road centre line encoding transformed by space syntax software and centralities metrics quantitative spatial characterisation of road network shape/accessibility and socio-economic variables to investigate the association with commercial rental values of a large sample of commercial property located in designated sub-centres.
Findings show that a sub-centre can be spatially distinguished from its non-centre surroundings. A sub-centrality spatial signature: sub-centre spatial and socio-economic typology are identified. Of the two main space syntax spatial variables associated with the sub-centres signatures, one would be the remit or urban design (local spatial scale, walking scale <= 800 m) and the other (meso-scale, <= 2,000 m) would be the remit of transport planning.
Publication 4: Zhang, L., Chiaradia, A.* & Zhuang, Y. A., 2015. Configurational Accessibility Study of Road and Metro Network in Shanghai. In: Q. Pan & J. Cao, eds. Recent Developments in Chinese Urban Planning. Heidelberg: Springer, pp. 219-245.
This research deployed standard road centre line encoding, metro network topological encoding and 2D spatial Design Network Analysis (sDNA) software quantitative spatial characterisation of road network and metro network shape/accessibility to investigate the probability density function of spatial distribution of metro system access points, bus access points and commercial land use in a Mega City.
The research shows the uneven spatial distribution of metro access points, bus access points, and commercial land use in Shanghai, with 60-70% associated with the top three deciles of road and metro network shape/accessibility. The main contribution is the comprehensive analysis of the spatial distribution of transport and land-use resources in a mega-city context.
Publication 5: Zhang, L. & Chiaradia, A.*, 2019. Three-dimensional Spatial Network Analysis and Its Application in a High Density City Area, Central Hong Kong (In Chinese). Urban Planning International, 33(1), pp. 46-53.
This research used 3D pedestrian standard path centre line network encoding and 3D sDNA software quantitative spatial characterisation of outdoor and indoor multi-level pedestrian network shape/accessibility to investigate their association with pedestrian flow level in one of the most complex multi-level-built environments.
The research reveals a high association between the standard spatial characterisation of outdoor and indoor multi-level pedestrian network shape/accessibility and pedestrian flow levels in a complex built environment. The main contribution is the demonstration of the interdependence between outdoor and indoor pedestrian networks in a high-density urban context.
Publication 6: Chiaradia, A.*, Sieh, L. and Plimmer, F., 2017. Values in urban design: A design studio teaching approach. Design Studies, 49, pp. 66-100.
The paper refers to physical configurations in general and the movement network that UNeMos are measuring. It articulates a theoretical bridge between the technicalities of measuring urban morphology and the creative application of resulting insights about the impact of any proposed, designed urban shape on the performance of the urban ‘place’ of which it is a part. The basis of the bridge is the concept of value. This is not simply ‘price’ but an interdisciplinary social scientific compound construct inspired by an extensive anthropological meta-review of value: “that which matters, and the extent to which that matters.”
The research establishes a theoretical bridge between urban morphology measurement and urban design creativity through the concept of value, which is adapted from Graeber’s general conceptualisation. The main contribution is developing a value-based approach to urban design, as demonstrated through the analysis of student work in an urban design studio.
Publication 7: Chiaradia, A., Cooper, C., Webster, C., 2011, spatial Design Network Analysis Software, & Cooper, C.H. and Chiaradia, A.J., 2020. sDNA: 3D spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX, 12, p.100525.
Spatial Design Network Analysis (sDNA) is a toolbox for 2D and 3D spatial network analysis, especially street/path/urban network analysis, motivated by a need to use standard network links/nodes as the principal unit of analysis to analyse existing and projected network data. sDNA is usable from QGIS & ArcGIS geographic information systems, AutoCAD, Rhino Gh, and the command line via its own Python API. It computes measures of accessibility (reach, mean distance/closeness centrality, gravity), flows (bidirectional betweenness centrality) and efficiency (circuity) as well as convex hull properties, localised within lower- and upper-bounded radial bands. Weighting is flexible and can use geometric properties, data attached to links, zones, matrices or combinations of the above. Motivated by a desire to base network analysis on route choice and spatial cognition, distance can be network-Euclidean, angular, a mixture of both, custom, or specific to cyclists (avoiding slope and motorised traffic). In addition to statistics on network links, the following outputs can be computed: geodesics, network buffers, accessibility maps, convex hulls, flow bundles and skim matrices.
Further tools assist with network preparation and calibration of network models to observed data. To date, sDNA has been used mainly for urban network analysis by academics and city planners/engineers for tasks including predicting pedestrian, cyclist, vehicle and metro flows and mode choice and quantifying the built environment for epidemiology and urban planning & design. The main contribution is developing a user-friendly and flexible software tool that supports various types of 3D network analysis, including accessibility, flows, efficiency measures, and various output formats and tools.
The commentary critically introduces, compares, and analyses various spatial models of distance using the closeness centrality of a network, combinations of transport network encoding and topological, Euclidean, angular and hybrid distances for their capacity and limitations to discriminate transport network layout. It contextualised the issues related to how and what could be “counted so as to reveal the differences between one settlement structure and another?” (Hillier & Hanson, 1984) in 2D or 3D to capture urban design values.
The main findings are as follows:
• Topologic distance is inferior at measuring and discriminating distinct layout configurations of the transport networks.
• To a very good extent, Euclidean distance measures and discriminates distinct layout configurations of transport networks, yet mainly grid-like layout.
• Angular distance remedies the issues of Euclidean distance related to a deformed grid yet introduces errors that can be resolved by Hybrid distance.
The link/node model of encoding transport network combined with closeness centrality of the network using spatial models of distance seems valid in discriminating distinct layout configurations of 2D and 3D transport networks. The publications’ original contributions demonstrate that these techniques empirically capture 2D and 3D urban design values
